Cees Taal

My experience lies in the area of sensor data processing and analysis for a wide variety of applications including digital hearing instruments (audio, speech), IoT (temperature, proximity sensing) and wearable medical devices (accelerometry, electrography). I prototype my stuff in Python/Matlab and make embedded real-time implementations in C. Currently I’m working as an R&D algorithm developer at Quby, who builds the Toon. I love to combine both industry and academia in my daily work.

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Bio: Cees studied Music Technology at the Utrecht school of Arts, Hilversum, the Netherlands and graduated in 2004. During this study he visited STEIM, the Netherlands as a C++ music-dsp programmer and the audio lab, University of York, U.K., where he worked on physical modeling of drums. In 2008 Cees went to the Delft University of Technology, the Netherlands, where he obtained an M.Sc. in Computer Science (2008) and a Ph.D. in speech signal processing (2012).  The title of his thesis was “Prediction and Optimization of Speech Intelligibility in Adverse Conditions” which was a collaboration with Oticon A/S hearing aids. Subsequently, he held postdoc positions in the Sound and Image Processing Lab, KTH, Sweden in the field of Digital Signal Processing in Audiology (AUDIS) and in the ENT-department, Leiden University Medical Center, the Netherlands, in the field of speech processing applied to cochlear implants in collaboration with Advanced Bionics. After academia he shifted to industry where he was appointed as a research scientist with Philips Research, Eindhoven working in the field of biomedical signal processing. Currently, he works at Quby, Amsterdam where he develops real-time algorithms for the Toon smart thermostat. In 2016 Cees received a best paper award from the IEEE signal processing society for one of his papers on predicting intelligibility from noisy processed speech signals.